{"id":297,"date":"2022-11-30T23:34:50","date_gmt":"2022-11-30T23:34:50","guid":{"rendered":"https:\/\/blogschapman.wpenginepowered.com\/engineering\/2022\/11\/30\/machine-learning-strategist-lauren-perry-shares-trusted-ai-framework-with-engineering-students-faculty\/"},"modified":"2026-07-23T20:43:04","modified_gmt":"2026-07-23T20:43:04","slug":"machine-learning-strategist-lauren-perry-shares-trusted-ai-framework-with-engineering-students-faculty","status":"publish","type":"post","link":"https:\/\/blogs.chapman.edu\/engineering\/2022\/11\/30\/machine-learning-strategist-lauren-perry-shares-trusted-ai-framework-with-engineering-students-faculty\/","title":{"rendered":"Machine Learning Strategist Lauren Perry Shares Trusted AI Framework with Engineering Students, Faculty"},"content":{"rendered":"<p><a href=\"https:\/\/blogs.chapman.edu\/engineering\/wp-content\/uploads\/sites\/72\/2022\/11\/Perry2.jpg\" rel=\"attachment wp-att-299\"><img loading=\"lazy\" decoding=\"async\" class=\"alignleft wp-image-299\" src=\"https:\/\/blogs.chapman.edu\/engineering\/wp-content\/uploads\/sites\/72\/2022\/11\/Perry2.jpg\" alt=\"\" width=\"364\" height=\"485\" srcset=\"https:\/\/blogs.chapman.edu\/engineering\/wp-content\/uploads\/sites\/72\/2022\/11\/Perry2.jpg 384w, https:\/\/blogs.chapman.edu\/engineering\/wp-content\/uploads\/sites\/72\/2022\/11\/Perry2-225x300.jpg 225w\" sizes=\"auto, (max-width: 364px) 100vw, 364px\" \/><\/a>Recently, Artificial Intelligence (AI) and Machine Learning Strategist Lauren Perry educated the <a href=\"https:\/\/www.chapman.edu\/engineering\/index.aspx\">Fowler School of Engineering<\/a> (FSE) community on noteworthy failures among AI algorithms. Perry spoke before a packed crowd in the Ideation Zone, outlining what went wrong in these examples and how to introduce frameworks designed to prevent history from repeating itself.<\/p>\n<p>Perry began her talk by asking students and faculty to share AI failures they had heard of, from unreliable facial recognition software to vehicles crashing while on autopilot. The historic road to developing AI is lined with failures like these; Perry approached this understanding with urgency, expressing the importance of recognizing what caused these past mistakes.<\/p>\n<p>\u201cAlgorithms don\u2019t always work, and when they don\u2019t, it can be funny\u2013such as creating art that depicts cooked salmon in a river\u2013all the way to actual disastrous consequences,\u201d Perry stated.<\/p>\n<p>Throughout the conversation, Perry highlighted mistakes to look out for when developing AI. Her list ranged from small-scale failures\u2013such as when misunderstood data input caused a sports camera to mistake a referee\u2019s bald head for a soccer ball\u2013to dangerous or even fatal errors, the most devastating of which involved plane crashes resulting from an uncontrollable algorithm that pilots could not override. Understanding how these real-world failures occur in the first place, Perry explained, is the preliminary step in algorithm development.<\/p>\n<blockquote><p><strong><em>\u201cThere are real-life things that are happening in your data, not just purposeful, adversarial inputs that can drastically affect your response, so you want to test and make sure that you\u2019re making the right decisions about your data so that these things can\u2019t happen,\u201d Perry said.<\/em><\/strong><\/p><\/blockquote>\n<p>How, then, can engineers actively prevent these errors from occurring in new algorithms? <a href=\"https:\/\/www.chapman.edu\/our-faculty\/erik-linstead#gsc.tab=0\">Dr.<\/a> <a href=\"https:\/\/www.chapman.edu\/our-faculty\/erik-linstead#gsc.tab=0\">Erik Linstead, Senior Associate Dean of FSE<\/a>, invited Perry to help address this core concern, not only among students and faculty, but also everyday people who may one day use this technology.<\/p>\n<p>\u201cA natural question everyone is interested in is \u2018how do we know we can trust AI, how do we know that something is safe to do?\u2019 Finding someone who\u2019s working with these ideas like her is important,\u201d said Linstead. \u201cHer ability to tie in the concepts to real-world failures made it a really useful talk.\u201d<\/p>\n<p>Perry\u2019s work as a Senior Project Engineer at The Aerospace Corporation focuses around the formation and application of trusted AI frameworks. These are designed to help engineers pinpoint errors long before a new system makes its debut, especially when protecting the safety and investments of others is a top priority.<\/p>\n<p>During the talk, Perry shared her framework with students and faculty. Its structure highlights four core foci: defining needs to gauge whether AI is the most appropriate solution, specifying objectives in data, assessing against trust attributes, and deploying and maintaining trust in operations. In applying this concise framework, engineers like Perry can gain the confidence that their technology will perform tasks correctly with good intentions.<\/p>\n<p>This understanding is vital within Perry\u2019s field of space domain awareness.<\/p>\n<blockquote><p><strong><em>\u201cWe bring a lot of AI and machine learning into the space industry as part of my job at Aerospace,\u201d Perry shared. \u201cYou\u2019re putting AI and machine learning on these multimillion-dollar spacecraft or multibillion-dollar programs. Instead of just applying an algorithm, it\u2019s about understanding the different facets of what the algorithm does in order to actually trust it.\u201d<\/em><\/strong><\/p><\/blockquote>\n<p>Linstead cited Perry\u2019s tangible experience outside of academia as a valuable asset to the conversation. \u201cShe is actually applying these concepts in-industry in really interesting use cases for big projects. It\u2019s fun especially for the students to see that real-world connection,\u201d Linstead explained.<\/p>\n<p>Perry\u2019s talk concluded with a note of encouragement, reminding FSE students and faculty of the purpose behind her words: to instill in them the understanding required to design meaningful, effective, and trustworthy AI. \u201cI hope that when you are creating algorithms going forward, you\u2019re doing more than just looking at your accuracy metrics,\u201d Perry said. \u201cThat way, your algorithms can actually make it into operations and make a difference out there.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Aerospace Corps Senior Project Engineer Discusses Historical AI Failures and How to Prevent Them<\/p>\n","protected":false},"author":66,"featured_media":298,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center 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center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"custom_author_name":"Lauren Sieberg ('25, Creative Writing & English)","chapman_pin_hero_slider":"","footnotes":""},"categories":[7,4],"tags":[57,58,59],"class_list":["post-297","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-career","category-events","tag-artificial-intelligence","tag-lauren-perry","tag-machine-learning-strategist"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Fowler School of Engineering | Chapman Blogs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blogs.chapman.edu\/engineering\/2022\/11\/30\/machine-learning-strategist-lauren-perry-shares-trusted-ai-framework-with-engineering-students-faculty\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine Learning Strategist 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